This research project will objectively quantitate human sleep EEG and EOG data using an automated data analysis system consisting of a sleep analyzing hybrid computer (SAHC) interfaced with a PDP-8e minicomputer in order to increase the amount of information extracted from sleep data, provide a more complete description of the sleep process than is provided by sleep tagging, and to develop objective and sensitive indices for monitoring changes in EEG. The SAHC employs analog filtering, period discrimination, amplitude detection and pattern recognition to mimic an electroencephalographer in detecting characteristic waveforms in the sleep EEG. The analysis of the all night sleep records will furnish minute by minute summaries of the amount of alpha, beta, and delta times plus the number of sleep spindles and rapid eye movements. Data microanalysis will describe the amplitude and frequency of individual alpha, beta, and delta waves. Quantitative data will be obtained from an ontogeny study, consisting of five subjects in each of five age groups from 13 to 80 years of age. Also, the acquired data will determine sensitive indices for monitoring changes in the sleep EEG. The effect of the chronic administration of a mild hypnotic on the sleep EEG will be evaluated and the sleep EEG's of a group of insomniacs will be quantified. The data will be analyzed to determine their relationships to the conventional sleep stage classifications, and in addition, the time course of the various parameters will be analyzed, and mathematical models developed to describe the activities. The interdisciplinary research team consists of members of the Departments of Electrical Engineering, Psychiatry, Psychology, and Statistics.